The present invention relates generally to the field of imaging systems. In particular, the invention relates to a system and method for reconstructing image data acquired from a computed tomography imaging system.
Computed Tomography (CT) scanners operate by projecting fan shaped or cone shaped X-ray beams through an object. The X-ray beams are generated by an X-ray source, and are generally collimated prior to passing through the object being scanned. The attenuated beams are then detected by a set of detector elements. Each detector element produces a signal based on the intensity of the attenuated X-ray beams, and these signals are processed to produce projection data, also called sinogram data. By using reconstruction techniques, such as filtered backprojection, useful images are formed from the projection data.
A computer is able to process and reconstruct images of the portions of the object responsible for the radiation attenuation. As will be appreciated by those skilled in the art, these images are computed by processing a series of angularly displaced projection data. These data are then reconstructed to produce reconstructed images, which are typically displayed on a cathode ray tube, and may be printed or reproduced on film.
A number of techniques have been employed to improve the image quality of reconstructed image data. Some of these techniques include, for example, pre-processing the projection data by either correcting for physical effects such as beam hardening, partial volume averaging and scatter, or by using adaptive filtering techniques. Adaptive filtering techniques improve the image quality by smoothing or filtering projection data adaptively, wherein the amount of smoothing applied to a given projection data element is based upon the attenuation or on the associated noise level of the projection data element. The entire sinogram or set of projection data elements is pre-processed in this manner and then reconstructed, typically using a conventional filtered backprojection reconstruction technique. As is known by those skilled in the art, adaptive filtering techniques influence one or more image quality parameters such as, for example, spatial resolution and image noise, to improve the overall image quality of the reconstructed image. However, existing adaptive filtering techniques are independent of the pixel (or a group of pixels) being reconstructed. That is, the entire sinogram or set of projection data elements are initially filtered with an adaptive filter, and then the adaptively-filtered sinogram is used to reconstruct the entire image. In addition, existing adaptive filtering techniques are derived based on empirical rules.
Therefore, there exists a need in the art for a technique that provides for improved image data quality while optimally meeting one or more desired image quality properties.